By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
In this paper we propose an algorithm for image recovery where completely lost blocks in an image/video-frame are recovered using spatial information surrounding these blocks. Our...
Image blur and noise are difficult to avoid in many situations
and can often ruin a photograph. We present a novel
image deconvolution algorithm that deblurs and denoises
an ima...
C. Lawrence Zitnick, David J. Kriegman, Neel Joshi...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...